Episode 27 - AST: An Endangered Species
December 6, 2025
Show Notes
Summary
In this episode, Adam and Martin discuss the evolving landscape of event modeling and event sourcing, highlighting the challenges of adoption, the importance of in-person workshops, and the impact of AI on software development. They explore how event modeling can serve as a powerful prototyping tool, bridging the gap between business requirements and technical implementation. The conversation emphasizes the need for continuous improvement in software practices and the significance of understanding the business domain to drive successful outcomes. In this conversation, Adam Dymitruk and Martin discuss the integration of AI in software development, particularly focusing on event modeling and sourcing. They explore the shift from traditional coding practices to more efficient methods, the impact of AI on development speed and clarity, and the evolving role of IDEs. The discussion also touches on the economic implications of AI advancements and the necessity (or lack thereof) of event catalogs in modern development practices.
Takeaways
Event modeling is gaining traction but faces adoption challenges.
In-person workshops foster better connections and understanding.
AI tools are changing the landscape of software development.
Prototyping can be effectively done through event modeling.
Event modeling provides a clear picture of business requirements.
The disconnect between business and development needs to be addressed.
Refactoring tools enhance productivity in software development.
Event modeling should be a continuous process, not a one-time event.
Understanding the business domain is crucial for successful software development.
Event modeling can help bridge the gap between business needs and technical implementation. AI is a reflection of human practices in coding.
The transition from JSON to more efficient formats like Toon is underway.
Event modeling benefits significantly from AI advancements.
Cultural shifts in development practices are essential for AI integration.
Lightweight tools are preferred over heavy IDEs for efficiency.
Local models can streamline development processes.
AI’s economic implications are reshaping the industry.
Event catalogs may not be necessary with effective event modeling.
Understanding the story behind changes in code is crucial.
Preparation for discussions may not always be necessary.
Chapters
00:00 Introduction and New Beginnings
01:57 Event Modeling Adoption Challenges
05:59 The Importance of In-Person Workshops
10:07 The Role of AI in Event Modeling
14:03 Prototyping with Event Modeling
18:06 The Shift in Software Development Paradigms
22:07 The Future of Event Modeling and AI
26:07 Refactoring and Productivity in Development
30:04 The Disconnect Between Business and Development
34:07 Event Modeling as a Continuous Process
39:30 Legacy Code and AI Integration
41:04 The Shift from JSON to More Efficient Formats
43:03 AI’s Impact on Event Modeling and Sourcing
44:59 The Cultural Shift in Development Practices
48:01 The Future of IDEs and AI Tools
50:51 The Role of Local Models in Development
53:45 The Evolution of AI and Its Economic Implications
57:11 Event Catalogs vs. Event Modeling
01:00:59 The Future of AI in Development